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Superconducting foams of YBa$_2$Cu$_3$O$_y$ (YBCO) are proposed as trapped field magnets or supermagnets. The foams with an open-porous structure are light-weight, mechanically strong and can be prepared in large sample sizes. The trapped field distributions were measured using a scanning Hall probe on various sides of an YBCO foam sample after field-cooling in a magnetic field of 0.5 T produced by a square Nd-Fe-B permanent magnet. The maximum trapped field (TF) measured is about 400 G (77 K) at the bottom of the sample. Several details of the TF distribution, the current flow and possible applicatons of such superconducting foam samples in space applications, e.g., as active elements in flux-pinning docking interfaces (FPDI) or as portable strong magnets to collect debris in space, are outlined.

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Abstract Introduction: Antimicrobial resistance (AMR) is a recognised public health threat today globally. Though many active and passive stewardship strategies are employed to counter AMR clinically, educating school going children on AMR could be a futuristic cost-effective measure to minimize AMR development. We hypothesised NICE’s e-bug module to class VII school students on AMR determinants. Methodology: A prospective non-randomized intervention study on 327 students belonging to 9 schools of class VII around Manipal town, Udupi district, Karnataka state, India were included for the study. 10 questions on AMR determinants extracted from NICE’s e-bug program were quizzed in written as pre-test followed by an education intervention on the same questions followed by a post-test to end the session. Descriptive statistics to estimate epidemiological characteristics, Wilcoxon Signed Ranks and Kruskal-Wallis tests were applied to analyse statistical significance of pre/post-test performance scores for the 10 questions and between schools respectively Results: Students had inadequate knowledge on 7 AMR determinants (antimicrobial indication, its course, hand hygiene, fermentation, spread of infection, microbial multiplication and characteristics of microbe) when analysed for post-test performance (p<0.05). Comparison of post-test performance of 9 participating schools revealed statistical significance (p<0.05) for 3 questions (definition on antimicrobial, cover while cough/sneezing and microbial characteristics) Conclusion: Although students exhibited sub-optimal knowledge on few AMR determinants, they showed keenness to learn exhibited by their performance. Our findings and previous similar studies from Europe are suggestive of early pedagogic interventions on AMR through inclusion of such education modules in the curriculum could be potential tool for AMR prevention for future generations.

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Background: Gut-Brain-Axis provides bidirectional communicational route; imbalance of which can have pathophysiological consequences. It is a frontier in autism research, affects 85% of autistic children (NIH report). Their microbiome has few overall microbes and smaller number of health promising microbes than their neurotypical peers. We hypothesize autism gut might play a role in manifestation of autism behaviours and on treatment, can revert back to normal behaviour considerably. The aim is to better understand to what degree gut microbiota of autism subjects differs from controls and identify bacterial species present exclusively in autism. Materials and Methods: 16s-rRNA-sequence of autism-subjects were retrieved from the American Gut Project Archive. Taxonomic assignment was inferred by similarity based methods using Quantitative Insights Into Microbial Ecology (QIIME). Species abundance was characterized and co-occurrence network was built to infer species interaction using measures of diversity. Statistical parameters were considered to validate the findings. Result: A total of 206 (1.8%) of American Gut Project datasets onstituted of autistic samples. Various bacteria such as Akkermansia sp., and Prevotella sp., were harboured in higher abundance in autistic children with statistical significance than in controls. Conclusion: These findings indicate connecting-link between gut-microbiome-brain-axis and autistic behaviour which can result in improved management

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Security has become a critical issue in today’s highly distributed and networked systems. Network intrusion detection systems (NIDSs), especially signature-based NIDSs, are being widely deployed in a distributed network environment with the purpose of defending against a variety of network attacks. Most of the commercially available NIDSs are software based and rely on pattern matching to extract the threat from network traffic. The increase in network speed and traffic may make existing algorithms to become a performance bottleneck. Therefore it is very necessary to develop faster and more efficient pattern matching algorithm in order to overcome the troubles on performance of NIDSs. Therefore, we propose a multi fusion pattern matching algorithm for Network Intrusion Detection Systems. The results obtained in percentages from the proposed fusion algorithm given better values in terms processing time in milliseconds than the existing algorithms when data English text are applied to evaluate the fusion performances.

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